Zobrazeno 1 - 10
of 128
pro vyhledávání: '"YONGQIANG LYU"'
Autor:
Jian Song, Jintao Wang, Fang Yang, Hongming Zhang, Chao Zhang, Hui Yang, Changyong Pan, Xiaofei Wang, Yongqiang Lyu, Luoxi Hao
Publikováno v:
Intelligent and Converged Networks, Vol 3, Iss 3, Pp 229-243 (2022)
Intelligent lighting has attracted lots of research interests to investigate all the possible schemes to support this need as human has spent more and more time indoor. Semiconductor-based illumination network is an ideal bearer to carry on this miss
Externí odkaz:
https://doaj.org/article/6f11dc76570c407dbdfa96a5fb9a53a0
Publikováno v:
Mobile Networks and Applications. 27:1642-1658
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba91afc1b8f9e19b4179df7a470c176e
https://doi.org/10.1007/s11036-021-01868-5
https://doi.org/10.1007/s11036-021-01868-5
Autor:
Jinxiao Wu, Xiangyang Ji, Yongqiang Lyu, Xuanshu Luo, Yan Meng, Eric Morales, Dongsheng Wang, Xiaomin Luo
Publikováno v:
IEEE Transactions on Mobile Computing. :1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91fadb9fa4a0fd1e75d0344fbb65289b
https://doi.org/10.1109/tmc.2022.3214846
https://doi.org/10.1109/tmc.2022.3214846
Autor:
Pengfei Qiu, Qiang Gao, Dongsheng Wang, Yongqiang Lyu, Chunlu Wang, Chang Liu, Rihui Sun, Gang Qu
Publikováno v:
Proceedings of the 28th Asia and South Pacific Design Automation Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95f28bab998b304dc3e5680b34a6b45d
https://doi.org/10.1145/3566097.3567917
https://doi.org/10.1145/3566097.3567917
Autor:
Pengfei Qiu, Qiang Gao, Dongsheng Wang, Yongqiang Lyu, Chang Liu, Xiaoyong Li, Chunlu Wang, Gang Qu
Publikováno v:
2022 Asian Hardware Oriented Security and Trust Symposium (AsianHOST).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da2fb7c992d3f8ddcd15a6303951f906
https://doi.org/10.1109/asianhost56390.2022.10022280
https://doi.org/10.1109/asianhost56390.2022.10022280
Publikováno v:
2022 7th IEEE International Conference on Data Science in Cyberspace (DSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b7f151755bccf43bc9633f12f1bef5a
https://doi.org/10.1109/dsc55868.2022.00015
https://doi.org/10.1109/dsc55868.2022.00015
Publikováno v:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 40:1130-1143
Intel software guard extensions (SGX) increase the security of applications by enabling them to be performed in a highly trusted space (called enclave ). Most state-of-the-art attacks on SGX focus on either mining the software vulnerabilities in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8185bf6887b1376c3427543f4b635160
https://doi.org/10.1109/tcad.2020.3024853
https://doi.org/10.1109/tcad.2020.3024853
Publikováno v:
IEEE Transactions on Services Computing. 14:606-613
The decision of request mapping—which server to handle user request and response routing—which transit route to carry response back to user has great impact on the performance and cost of Content Delivery Networks (CDNs). Request mapping and resp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22ee324ab5d4db466f7744868ffc7d02
https://doi.org/10.1109/tsc.2018.2796567
https://doi.org/10.1109/tsc.2018.2796567
Publikováno v:
GetMobile: Mobile Computing and Communications. 24:30-33
Based on the concept of hardware separation, ARM introduced TrustZone to build a trusted execution environment for applications. It has been quite successful in defending against various software attacks and forcing attackers to explore vulnerabiliti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f15d7ba4def9ed66b79aba0c15f04fe4
https://doi.org/10.1145/3427384.3427394
https://doi.org/10.1145/3427384.3427394
Autor:
Shangming Cai, Yongqiang Lyu, Guangquan Xu, Haixia Wang, Athanasios V. Vasilakos, Xi Zheng, Dongsheng Wang
To reduce uploading bandwidth and address privacy concerns, deep learning at the network edge has been an emerging topic. Typically, edge devices collaboratively train a shared model using real-time generated data through the Parameter Server framewo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35ee4c73b6543659c5ef5ff1cd65066b
https://hdl.handle.net/10453/156337
https://hdl.handle.net/10453/156337
